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Amiya Kumar Tripathy
University of Mumbai
Computer Science & IT Electrical & Electronics Engineering

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Journal : International Journal of Electrical and Computer Engineering

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Opinion mining using combinational approach for different domains Jyoti Sandesh Deshmukh; Amiya Kumar Tripathy; Dilendra Hiran
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 4: August 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (707.593 KB) | DOI: 10.11591/ijece.v9i4.pp3307-3313

Abstract

An increase in use of web produces large content of information about products. Online reviews are used to make decision by peoples. Opinion mining is vast research area in which different types of reviews are analyzed. Several issues are existing in this area. Domain adaptation is emerging issue in opinion mining. Labling of data for every domain is time consuming and costly task. Hence the need arises for model that train one domain and applied it on other domain reducing cost aswell as time. This is called domain adaptation which is addressed in this paper. Using maximum entropy and clustering technique source domains data is trained. Trained data from source domain is applied on target data to labeling purpose A result shows moderate accuracy for 5 fold cross validation and combination of source domains for Blitzer et al (2007) multi domain product dataset.
Co-Authors Dilendra Hiran Jyoti Sandesh Deshmukh